[Numpy-discussion] quadratic function

[Robert Kern]

On Thu, Oct 28, 2010 at 06:38, Brennan Williams
<brennan.williams at visualreservoir.com> wrote:
>  I have used both linear least squares and radial basis functions as a
> proxy equation, calculated from the results of computer simulations
> which are calculating some objective function value based on a number of
> varied input parameters.
>
> As an alternative option I want to add a quadratic function so if there
> are parameters/variables x,y,z then rather than just having a linear
> function f=a+bx+cy+dz I'll have f=a+bx+cx**2 + dxy + .... I'd like to
> have the option not to include all the different second order terms.

A = np.column_stack([
    np.ones_like(x),
    x, y, z,
    x*x, y*y, z*z,
    x*y, y*z, x*z,
])
x, res, rank, s = np.linalg.lstsq(A, f)

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco